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A Comparative Analysis of Superintendent, Principal, and Teachers' Perceptions of Accountability Systems. The purpose of this technical report is to develop a better understanding of the assessment and accountability practices and policies that educators are implementing in the classrooms, schools, and districts and to examine whether those policies are associated with perceived school and student improvements in achievement.\n\nThe study provides descriptive information about the need for schools and districts to effectively use data, how schools and districts use data to guide classroom practice, and the difference in data use based on the level of student proficiency in individual schools.

Increasingly, school board members from around the country are using data to help make good decisions about improving public education for all children. As school districts across the country grapple with how to think systemically and strategically about reaching student achievement goals and forging creative solutions from standardized test data, data-driven decision making can be used to inform board decisions.

Districts use new methods to learn what works best for kids
No longer is it viewed as acceptable for teachers to deliver lectures, administer grades and expect their students to simply try harder. Teachers are increasingly being asked to use assessments and collect data on student learning to gauge whether their methods are succeeding and what more needs to be done.

With over 420,000 students and more than 600 schools, Chicago Public Schools finds itself in all three stages of data-driven decision making at once: collection, analysis, and action. The master data warehouse is nearly complete and will be rolled out in fall 2007 along with systems for specialized services management, curriculum instruction, and student information. Analysis is handled by the Office of Research and Analysis and published on a dedicated research Web site (http://research.cps.k12.il.us). The Principals Technology Leadership Institute (PTLI) is training principals in the art and science of using data for decision-making within their schools.

Like never before, today's classroom teachers routinely are being asked to collaboratively analyze student data, develop or implement new mandated curricula, and assess the effectiveness of these innovations. Ironically, few preservice preparatory or in-service professional development programs actively train classroom instructors in the use of team-based inquiry or collaborative data- driven problem solving. Framed within the context of the literature and governmental efforts to achieve school reform, this article describes one such in-service program, in practice at public and charter schools in high-need communities in New York City. The Inquiry Based School Improvement Program (IBSIP) was created and designed to help schools serving high-need communities in New York City engage in the types of team-based inquiry and data-driven problem solving needed to meet the everchanging institutional demands on these schools to improve.

Analyzing your data is a process you will want to involve your entire staff. There are a number of variables that will help you determine the best strategy for your school including the size of staff, organization of teams, availability of computers with Internet, and the amount of staff meeting time. The critical piece is that you model the importance of data analysis and that you involve (mandate) all staff in the process. The odds of teachers making the instructional changes needed for improved student achievement are much greater when the data and what it tells them about current achievement.

The momentum behind building high-quality data systems to harvest better information about student, school, and district performance has never been stronger. Although collecting data is essential, knowing how to analyze and apply this information is just as important for meeting the end goal of improving student achievement. The purpose of this study is to identify, quantify, and report on district-level processes that enable effective utilization of data to increase academic achievement at the classroom level.

Well before the idea of using data to manage schools gained prominence on the national stage, Oklahoma's Western Heights school district had made the ideal of real-time, data-driven decisionmaking a reality. Back in 2001, Superintendent Joe Kitchens was already being spotlighted for his focus on creating a longitudinal-data system that would give teachers in the 3,400-student district the ability to make quick decisions to improve student learning, while reducing the time spent compiling reports.

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From PBS 39 Education. What is data driven decsion making and why is it needed? Using data is critical in strategies for student achievement.

It seems like you can't go a whole week lately without hearing about some major data security breach that has made national headlines. For businesses, these data leaks are bad enough-but for schools, they can be especially costly, as network security breaches can put schools in violation of several federal laws intended to protect students' privacy.

This study from the Rand Corporation explores how teachers and principals use test score data, what features of its use are relevant to them, and what assistance is available to help them use the data for instructional decisionmaking.

The Pivot tables and chartsfeature in Excel lets educators begin disaggregating and analyzing data within seconds (literally) of receiving original data files from state departments, testing companies, and/or school districts. These ten tutorials show how to use what is perhaps the most powerful data analysis tool within Excel

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Karen Greenwood Henke: Presentation at the 12th Annual COSN Conference, San Francisco. Report on the COSN Data Driven Decision Making Initiative.

This report addresses some of these issues by summarizing findings from an exploratory study of the school-based assessment practices in a sample of elementary, middle, and secondary schools. The purposes of the study were twofold: (1) to add to the growing base of knowledge about how schools use student assessment data obtained from multiple sources to inform important decisions about programs, instruction, and individual students; and (2) to identify and describe the factors and conditions that make schools' use of the student assessment data more probable and valuable.

NCREL has gathered a selection of web-based tools for collecting information, ranging from checklists to surveys, and including information about software tools for data collection and analysis. A tutorial provides an overview of the use of data in school improvement; a bibliography and background section are also included.

Making data part of instructional planning can be challenging, especially if teachers are not used to thinking about assessment and data as a regular part of the process. This article offers helpful tips.

April 2008 : THE Journal. As each district progresses, it will face new challenges discerning what data is relevant, addressing tolerance for change among users, and figuring out how to respond now that data is driving its decision-making.
\nStage 1: Define the Outcomes
\nStage 2: Define the Questions
\nStage 3: Collect and Sort
\nStage 4: Extract Meaning
\nStage 5: Take Action
\nStage 6: Evaluate Outcomes, Modify as Needed

Everyone's talking about D3M. Use this guide to help prevent all that data from driving you nuts.